Emergent Mind

Abstract

Biometric authentication is one of the promising alternatives to standard password-based authentication offering better usability and security. In this work, we revisit the biometric authentication based on "fuzzy signatures" introduced by Takahashi et al. (ACNS'15, IJIS'19). These are special types of digital signatures where the secret signing key can be a "fuzzy" data such as user's biometrics. Compared to other cryptographically secure biometric authentications as those relying on fuzzy extractors, the fuzzy signature-based scheme provides a more attractive security guarantee. However, despite their potential values, fuzzy signatures have not attracted much attention owing to their theory-oriented presentations in all prior works. For instance, the discussion on the practical feasibility of the assumptions (such as the entropy of user biometrics), which the security of fuzzy signatures hinges on, is completely missing. In this work, we revisit fuzzy signatures and show that we can indeed efficiently and securely implement them in practice. At a high level, our contribution is threefold: (i) we provide a much simpler, more efficient, and direct construction of fuzzy signature compared to prior works; (ii) we establish novel statistical techniques to experimentally evaluate the conditions on biometrics that are required to securely instantiate fuzzy signatures; and (iii) we provide experimental results using a real-world finger-vein dataset to show that finger-veins from a single hand are sufficient to construct efficient and secure fuzzy signatures. Our performance analysis shows that in a practical scenario with 112-bits of security, the size of the signature is 1256 bytes, and the running time for signing/verification is only a few milliseconds.

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